chickymonkeys/laevenvalenciabankingcrises

A Stata Script to acquire the Laeven Valencia (2008, 2013, 2018) Systemic Banking Crises Database.

Systemic Banking Crises Database

This project provides a standalone script in Stata to download the original Laeven and Valencia (2020) Systemic Banking Crises Database from the IMF Working Paper Page. It computes the provided Excel Spreadsheet such that it creates a spell dataset (in .dta format) with an entry for each country experiencing a systemic banking crisis, the outcome of the crisis and flags for whether there are multiple crises other than the mentioned one (currency, sovereign debt, and sovereign debt restructuring).

UPDATED VERSION We complement the Laeven and Valencia (2020) Systemic Banking Crises Database with the Behavioral Finance and Financial Stability Project's (BFFS) Historical Database of Banking and Systemic Crises. This is based starting from the data in Reinhart and Rogoff (2009).

To uniquely identify countries, it consider the ISO-1366-1 Numeric code format, in a way that it allows to link the dataset to other sources. In Stata, this is straightforward through the user-written command kountry in Raciborski (2008).

Methodology and Definition

In the baseline database from Laeven and Valencia (2020), a systemic banking crisis is identified when two conditions are met:

1. Significant signs of financial distress in the banking system (as indicated by significant bank runs, losses in the banking system, and/or bank liquidations). This is a sufficient condition to date a systemic banking crisis when When the losses in the banking sector or liquidations are severe.

2. Significant banking policy intervention measures in response to significant losses in the banking system. Policy interventions are defined as:

   • deposit freezes and/or bank holidays;
   • significant bank nationalizations;
   • bank restructuring fiscal costs (at least 3% of GDP);
   • extensive liquidity support (at least 5% of deposits and liabilities to non-residents);
   • significant guarantees put in place; and
   • significant asset purchases (at least 5% of GDP).

In the BFFS Project database, we mark a banking crisis using by two types of events using the definition in Reinhart and Rogoff (2009), which are:

1. Bank runs that lead to the closure, merging, or takeover by the public sector of one or more financial institutions; and, if there are no runs,
2. The closure, merging, takeover, or large scale government assistance of an important financial institution (or group of institutions) that marks the start of a string of similar outcomes for other financial institutions.

To our means, only a combination of systemic and banking crisis in the BFFS Banking Crisis Database is admissible to mark the event as a crisis. We keep Laeven and Valencia (2020) as baseline, only adding missing crises and information about simultaneous inflation crises from the BFFS Database. In case of date conflict or overlapping, we prioritise Laeven and Valencia's information to the BFFS Project information.

Overall, there are no massive overlapping between the two datasets, and it is more the BFFS Project Dataset integrating the other with additional crises and correct ending years.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See installing and running for notes on how to run the script.

In the final dataset, it is possible to find the following variables:

• isocodes: the the country name encoded with ISO 3166-1 Numeric;
• fsysbank: the number of systemic banking crisis in spell format (increasing number);
• startyear: the starting year of the crisis;
• endyear: the ending year of the crisis (missing if still ongoing);
• yloss: the output loss due to the crisis measured in percentage of (potential) GDP;
• fcost: the fiscal cost of the crisis, as
  • percentage of GDP;
  • net fiscal cost in percentage of GDP;
  • percentage of financial sector assets;
• maxnpl: the peak of Non-Performing Loans as percentage of total financial sector assets;
• gsdebt: increase of public debt, as percentage of GDP;
• multiple crises flags:
  • hascurr equal to one in the presence of a currency crisis;
  • hassovdebt equal to one in the presence of a sovereign debt crisis;
  • hassovdebtres equal to one in the presence of sovereign debt restructuring;
  • hasinfl equal to one in the presence of a inflation crisis;
• dataset source flags:
  • lvsource equal to one if the event is present in Laeven and Valencia's;
  • rrsource equal to one if the event is present in the BFFS Project Historical Database of Banking Crises.

For additional information about the outcome of the crises and how they were measured by the original authors, see the working paper, the published article, and the definitions in the Reinhart and Rogoff's original book. Crises other than systemic banking and outcomes related to liquidity have been omitted.

Prerequisites

The script needs an internet connection to check whether the command kountry is installed and to download the dataset from the IMF website. For development purposes, just download the project directory in your computer, or feel free to fork the project.

Installing and Running

It is possible to just download the BankingCrisisDB.do script in the folder src of the project, copy it in a folder and run it within Stata.

The script creates three different folders:

• res: it contains the output dataset after running the script;
• log: it contains the ex-post .log file with the outcome of the script;
• temp: a temporary directory where the .zip file of the dataset is downloaded, extracted, and deleted after the script has finished.

Authors

• Alessandro Pizzigolotto - just the script - Norwegian School of Economics (NHH)

See the list of the original authors in the references.

License

This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details.

References

• Laeven, L., Valencia, F., 2018. Systemic Banking Crises Revisited (Working Paper No. 18/206), IMF Working Papers. International Monetary Fund, Washington, DC. Link.
• Laeven, L., Valencia, F, 2020. Systemic Banking Crises Database II. IMF Economic Review. Link.
• Raciborski, R. (2008). kountry: A Stata Utility for Merging Cross-country Data from Multiple Sources. The Stata Journal, 8(3), 390–400. Link.
• Reinhart, C. M., Rogoff. K. S., 2009. This Time is Different: Eight Centuries of Financial Folly. Princeton University Press, Princeton, NY.